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LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

@doytsujin
doytsujin / start_docker_registry.bash
Created September 7, 2021 16:36 — forked from u1i/start_docker_registry.bash
Start docker registry with letsencrypt certificates and Basic Auth
#!/usr/bin/env bash
# install docker
# https://docs.docker.com/engine/installation/linux/ubuntulinux/
# install docker-compose
# https://docs.docker.com/compose/install/
# install letsencrypt
# https://www.digitalocean.com/community/tutorials/how-to-secure-nginx-with-let-s-encrypt-on-ubuntu-16-04
<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<title>HTML5 GetUserMedia Demo</title>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0" />
</head>
<body>
<input type="button" title="开启摄像头" value="开启摄像头" onclick="getMedia();" /><br />